Vehicle Stabilization via a Self-Tuning Optimal Controller

Nowadays, using advanced vehicle control and safety systems in vehicles is growing rapidly. In this regard, in recent years new control systems, called VDC, have been introduced. These systems stabilize vehicle yaw motion, by yaw moment resulted from tire controlling forces. In this paper, an adaptive optimal controller applied to a vehicle to obtain a satisfactory lateral and yaw stability. To derive the control law, we use LQR method. Considering that various parameters are included in the controller structure, which their measurement is either expensive or practically impossible, a least squared estimator with variable forgetting factor is proposed to estimate them. To optimize the system and in order to exert the control yaw moment, an ABS brake system is implemented in a new architecture to distribute brake forces on wheels. The controller rules are derived based on the bicycle model and the estimator is designed based on the 7 DOE model of the vehicle. To simulate and evaluate the performance of the proposed controller the full vehicle model of the reference car in ADAMS/Car, with 214 DOE, is also implemented. Finally, the results of the vehicle response, equipped with the controller system, in a standard maneuver are presented.